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Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mobile Ad Hoc Networks. Jun Zhang and Brahim Bensaou The Hong Kong University of Science and Technology TWC 07. Outline. Introduction Correlative Power Constraints Core-PC Performance Evaluation Conclusion. - PowerPoint PPT Presentation
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1
Core-PC: A Class of Correlative Power Control Algorithms for Single Channel Mob
ile Ad Hoc Networks
Jun Zhang and Brahim Bensaou
The Hong Kong University of Science and Technology
TWC 07
Outline
Introduction Correlative Power Constraints Core-PC Performance Evaluation Conclusion
Introduction
The energy supply in wireless devices is limited by their battery capacity.
From measurements in real systems,– Packet processing only consumes a small fraction– The energy is consumed by the
transmission reception listening to the channels
Introduction
It is important to design power control algorithms that– Improving network throughput– Reducing energy consumption
Goal
To design power controlled MAC protocols – Throughput better than IEEE 802.11– Energy consumption smaller than IEEE 802.11
Introduction
All previous works on power control only consider the assignment of the transmission power of each frame separately.
Introduction
The authors derive a set of equations that correlate the transmission powers of RTS, CTS, DATA and ACK frames.
The authors derive a class of adaptive power control algorithms (Core-PC).
Correlative Power Constraints-- Basic Framework and Definitions
The transmission zone– The received power level of a frame from node i i
n its transmission zone is higher than or equal to κ.
The carrier sensing zone– The received power level of a frame from node i i
n its carrier sensing zone is higher than or equal to η.
Correlative Power Constraints-- Noise Level Estimation
When node A is receiving the CTS reply from a node B, we assume– The channel at node A is idle.– The node’s NAV is always set and the node is
silenced whenever it is in the transmission zone.– The thermal noise level is negligible.– The propagation model is the two ray ground
propagation model.
4
1),(d
rtg Path loss
Correlative Power Constraints-- Noise Level Estimation
Ravg : average transmission range
Pavg : average transmission power Δ : the density of simultaneous
transmitters outside A’s transmission zone
Δ is upper bounded by 2
1
avgR
Correlative Power Constraints-- Noise Level Estimation
ARTSR avg
avgANoise dx
xR
xPP
,
42,
2
According to the two ray ground propagation model
4/1)/( avgavg PR
ANoiseBARTS
avgANoise P
P
PP ,,
~
42
2
x
P
R
x avg
avg
Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception
BABRTSP ,
ABACTSP ,
The received power of RTS from node A to node B at location B
The received power of the CTS at node A must also fulfill the SIR requirement.
ANoiseABACTS PP ,, SIR threshold
),( ABgP
PP
avg
BARTSAB
CTS
The transmission power of CTS from node B to node A
A BRTS
CTS
Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception
A B
),( ABgP
PP
avg
BARTSAB
CTS
),( ABgP
PP
avg
ABCTSBA
DATA
),( ABgP
PP
avg
BADATAAB
ACK
Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception
To simplify the notation,
),(/),(min rsgrsP
),(/,max rsgP rs
xframe outgoingan ofpower ion transmissthe:xP
xframe incomingan ofpower ion transmissthe:xP
Correlative Power Constraints -- Requirements on Power Assignment for Frame Reception
))(),((min xrxsPPx
),( ABgP
PP
avg
BARTSAB
CTS
)(),(max OrOsavg
O PPPP I
Correlative Power Constraints -- Feasibility of Power Assignment
)),,(( max max,min
RTS
avgrsCTS
P
PPrsPP
)),,(( max max,min
CTS
avgrsDATA
P
PPrsPP
)),,(( max max,min
DATA
avgrsACK
P
PPrsPP
Correlative Power Constraints -- Feasibility of Power Assignment
maxmin ),( PrsP
rsavgP
P,
max
max2, PPP RTSavgrs
The minimal possible power assignment for a DATA frame in a successful 4-way handshake is
)),(,max( min,max rsPPP rsavg
Core-PC
Core-PC
In Algorithm 1, different combination of (PRTS,Pavg) lead to different power assignment algorithms.
Core-PC
Three alternative approaches may be adopted for setting the PRTS.– (a) Simple scenario
PRTS=Pmax
– (b) Symmetric scenario PRTS=PCTS
– (c) Minimum power scenario The RTS frame is transmitted at a power level such that th
e DATA transmission power is minimized.
Core-PC
Similarly, there are different ways of choosing the value of Pavg.
– (A) Worst case scenario Pavg=Pmax
– (B) Node-related adaptive scenario (i) initially Pavg=Pmax
(ii) all other nodes transmit their DATA frame at the same power level
– (C) Network-related adaptive scenario Pavg=0.9Pavg+0.1Pt transmission power
of a captured frame
Performance Evaluation
Simulator: NS-2 Routes: AODV Data rate: 11Mbps κ: 3.652e-10 Watts η: 1.559e-11 Watts ζ: 10dB Pmax: 0.2818 Watts
Rmax: 250m
Performance Evaluation-- Single Hop Scenario
50m
(I) 200m
(II) 150m
CBR traffic is generated and carried in UDP datagrams with a packet size of 512 bytes
Two packet sending rate:– 200 packets/s per sender– 400 packets/s per sender
Performance Evaluation-- Single Hop Scenario
Rate = 200 PKT/SECEND 200m
Performance Evaluation-- Single Hop Scenario
Rate = 400 PKT/SECEND 200m
Performance Evaluation-- Single Hop Scenario
Rate = 400 PKT/SECEND 150m
Performance Evaluation-- Multi-Hop Static Scenario
49 nodes 400*400 m2 area 7 flows are set between randomly chosen en
d-to-end source-destination pairs Packet size is 512 bytes
Performance Evaluation-- Multi-Hop Static Scenario
Performance Evaluation-- Multi-Hop Static Scenario
Conclusion
The correlations among the required transmission power of RTS/CTS/DATA/ACK– derived constraints that ensure the correct delivery
Using these constraints– The authors developed a class of correlative power
control algorithms
Simulations have shown the algorithm achieves– Higher throughput– Lesser energy consumption
Thank you